Document Type

Article

Publication Date

11-10-2016

Department

Center for Data Sciences, Department of Geological and Mining Engineering and Sciences

Abstract

Degrading permafrost conditions around the world are posing stability issues for infrastructure constructed on them. Railway lines have exceptionally low tolerances for differential settlements associated with permafrost degradation due to the potential for train derailments. Railway owners with tracks in permafrost regions therefore make it a priority to identify potential settlement locations so that proper maintenance or embankment stabilization measures can be applied to ensure smooth and safe operations. The extensive discontinuous permafrost zone along the Hudson Bay Railway (HBR) in Northern Manitoba, Canada, has been experiencing accelerated deterioration, resulting in differential settlements that necessitate continuous annual maintenance to avoid slow orders and operational interruptions. This paper seeks to characterize the different permafrost degradation susceptibilities present at the study site. Track geometry exceptions were compared against remotely sensed vegetation indices to establish a relationship between track quality and vegetation density. This relationship was used as a proxy for subsurface condition verified by electrical resistivity tomography. The established relationship was then used to develop a three-level degradation susceptibility chart to indicate low, moderate and high susceptibility regions. The defined susceptibility regions can be used to better allocate the limited maintenance resources and also help inform potentially long-term stabilization measures for the severely affected sections.

Publisher's Statement

© 2016 Priscilla Addison,et al., licensee AIMS Press. Article deposited here in compliance with publisher policies. Publisher's version of record: https://doi.org/10.3934/geosci.2016.4.329

Publication Title

AIMS Geosciences

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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